System and method for analyzing aerial photos

ABSTRACT

A system and method for analysis for analysis of aerial photos is disclosed. The method comprises receiving an aerial photo, calculating complexity values of aerial photos received, sorting the complexity values of the aerial photo, and displaying the aerial photos and analysis of the complexity values. The system comprises an input device for receiving aerial photos, a computing device for calculating complexity values of captured aerial photos, a computing device for sorting complex values of aerial photos, a storage device for storing internal database, and a comparator device.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims priority from PCT application No.PCT/IL01/01074, filed Nov. 21, 2001, and Israeli Patent Application No.146597, filed Nov. 20, 2001, each of which is hereby incorporated byreference as if fully set forth herein. PCT/IL01/01074 is currentlypending as U.S. national phase filing No. 10/445,213 and has beenpublished as U.S. Publication No. 2004/0236805.

BACKGROUND OF THE INVENTION

The present invention relates to analyzing aerial photos.

Aerial photos are photos taken from an aircraft or a satellite during atypically predominated flying route thus, providing a perspective viewof a usually large area. Consequently, aerial photos provideconsiderable amount of information regarding the surface captured by thephotograph. Aerial photos capture structural layout of the surface andobjects located on the surface within the photo's frame. The photos areused for mapping areas for civil engineering matters such as planningroads, bridges and habitation locations. Other purposes can be fortracking changes over a period of time by comparing previouslyphotographed aerial photos to current updated photograph of the samesurface location. Correspondingly, aerial photos can track position ofobjects located on a surface and their advancement over a period oftime. Hence, aerial photos are used for military surveillance of hostileobjects such as vehicles, tanks, artillery guns, anti-aircraft guns andthe like. The accuracy and magnitude of objects that can be detectedwithin an aerial photo is subject to the height of the aircraft and theresolution provided by the camera. The resolution and clarity of a photois also subject to the camera used and the clarity of the intermediatemedium (e.g. air) affected by the time of day, weather, etc. as well asother environment factors.

Aerial photos are usually large and capture a large surface area andconsequently a considerable amount of data. The considerable amount ofdata raises the problem of comprehending and processing all the saiddata within a reasonable period of time. Furthermore, the objectscaptured occasionally have low resolution and require expertiserecognition for determining the character of the said object. One mannerof interpreting an aerial photo is the manual way. The manual wayrequires expertise manpower that reviews in detail for pertinent objectswithin the photo's frame and reports its findings to an interestedfactor such as a mapping center agency, military intelligence agency,etc. The manual way is time consuming and is generally insufficient andimpractical when aerial photos are large and the period of time islimited. Another way for interpreting an aerial photo is by combing themanual way with a Pattern Recognition Method (PRM). According to thisway of interpreting the first stage is executing the PRM and the secondstage is by executing the said manual way. The PRM is operated withincomputerized surrounding that has the ability to recognize the presenceof an object on a photo that can be easily distinguished from itssurroundings, such as a ship in the ocean or a regiment of tanksconcentrated at one base in a desert and the like. The PRM operatingwithin a computerized environment provides fragments of the aerial phototo be examined according to the manual way. The fraction received fromthe operation of the RPM reduces the size of the aerial photo to beexamined within the next stage. Once the PRM is executed the secondstage of the manual way is executed upon the received fractions.However, the combination of the PRM and manual way does not provideaccurate results subject to the limitation of the PRM. The limitation ofthe PRM is due to the method of recognition of important objects withinan aerial photo, which often ignores important objects that are notrecognized, by this method.

There is therefore a need in the art for a method and system forrecognizing and analyzing important objects within aerial photosproviding rapid and accurate information.

SUMMARY OF THE INVENTION

A system and method for analysis for analysis of aerial photos isdisclosed.

The method comprises receiving an aerial photo, calculating complexityvalues of aerial photos received, sorting the complexity values of theaerial photo, and displaying the aerial photos and analysis of thecomplexity values.

The system comprises an input device for receiving aerial photos, acomputing device for calculating complexity values of captured aerialphotos, a computing device for sorting complex values of aerial photos,a storage device for storing internal database, and a comparator device.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a preferred embodiment of the present invention andparticularly an object recognition analysis system and method forrecognizing and analyzing areas containing objects generally and objectswithin aerial photos received by the system specifically.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

The present invention provides an object recognition analysis system andmethod (ORAS) for recognizing and analyzing areas containing objectsgenerally and objects within aerial photos received by the ORASspecifically. The present invention provides the use of the complexitydata analysis (CDA) system and method presented within PCT ApplicationPCT/IL01/01074, related patent application to the present invention,which is incorporated herein by reference. Thus, the ORAS provides theability of recognition and analysis of the existence of areas withobjects and objects using CDA. Furthermore the ORAS provides the abilityto compare two or more aerial photos or aerial photos fragments and toanalyze changes between said photos. In a further aspect of the presentinvention ORAS may operate in a combined manner with the PRM either forrecognition and analyzing objects or for tracing changes between two ormore aerial photos. The use of the CDA for recognition and analyzing ofobjects is performed by exploiting characteristic attribute of knownobjects and landscapes as viewed on an aerial photo. The complexityvalue of said characteristic attributes are inserted to the internaldatabase of the ORAS providing thresh-hold values used for comparisonand recognition of said objects by the CDA according to PCT ApplicationPCT/IL01/01074. The ORAS can be directed to a particular fragment withinan aerial photo and can perform a CDA for providing information, in onecase, whether there was a change of complexity value of the particularsection of the aerial photo in comparison to another and, in anothercase, to recognize and analyze existence of objects and particularobjects within an aerial photo. Accordingly, the ORAS can be directed tofragments frames within an aerial photo by a user, be used as afollowing stage of PRM for recognition and analysis of objects withinthe fragments frames received from activating the PRM, or a followingstage after activating any other method.

The ORAS activates complexity calculations on aerial photos or onfragments frames of aerial photos that were selected by a user,fragments received from executing PRM or any other method. After given acomplexity value by the complexity engine within the ORAS (according toPCT Application PCT/IL01/01074) the complexity value is compared, ifrequired, and sorted by the sorting device in accordance to suitableparameters received from the internal database of the ORAS. The ORASprovides recognition and analysis output of objects after the sortingdevice processed the complexity metric values given to objects withinthe fragment of the aerial photo. The ORAS will be better understoodrelating to FIG. 1.

FIG. 1 depicts a block diagram illustrating the GRAS, designated 10. TheORAS 10 includes an input device 20, a user interface 30, an externaldatabase 80, an output device 60, an internal database 70, a complexityengine 40 and a sorting device 50. The input device 20 is a device forcapturing aerial photos. According to one preferred embodiment the inputdevice 20 can be a scanner and the like. According to the preferredembodiment the input photo is presented to a user through the userinterface 30. The user interface 30 according to the present embodimentcan include a screen (not shown) and input device (not shown) such as apointing device. The user, according to the present embodiment canindicate fragments within the said photo for recognition and analysis.Additionally, the user, within the present embodiment, can insertparameters regarding basic definitions such as what percentage of thephoto to present, type of photos, etc. The parameters are inserted tothe internal database 70. The internal database 70 conveys parameters,inserted by user as well as others (according to PCT ApplicationPCT/IL01/01074), to the complexity engine 40. The complexity engine 40activates the CDA on the previously indicated fragments frames usingparameters received from the internal database 70. The complexity engine40 computes the complexity value 43 for the photo fragment and producesa complexity metric for each photo (i.e. for every area in the photo 47there are complexity parameters). The sorting device 50 sorts the areaaccording to their complexity value and sends the recognized andanalyzed relevant areas, within the previously indicated aerial photofragment by the user, to the user interface 30 for display. Concurrentlyfor receiving the recognized and analyzed relevant areas the userinterface 30 receives the said aerial photo fragment. According toanother embodiment the sorting device 50 can provide particular objectrecognition thus, presenting the user interface 30 with its analysis ofthe objects within the fragment. The output device 60 provides therelevant areas and the object recognition and analysis alongside withthe previously indicated aerial photo fragment to the user interface.The recognition and analysis results alongside with the relevant aerialphoto fragment are stored in the above embodiments within an externaldatabase 80 for further evaluation.

In another preferred embodiment the input device 20, such as a scanner,receives pairs of photos, each aerial photo photographed the samesurface location but at different time. The user interface 30 accordingto the present embodiment includes the same elements as the firstembodiment above, including a screen (not shown) and an input device(not shown) such as a pointing device. The user views the photo on theuser interface 30 and indicates the relevant fragment for analysis andcomparison. The user can insert parameters to the internal database 70through the user interface 30. The parameters can be regarding basicdefinitions such as what percentage of the photo to present, type ofphotos, etc. The internal database 70 receives the parameters, and sendsthe complexity engine 40 the appropriate calculation parameters foractivating a complexity calculation for each photo. The complexityengine 40 computes the complexity value 43 of the photos and produces acomplexity metric for each photo (i.e. each area within the photo 47 hasa complexity parameter). The complexity engine 40 calculates thedifference between the complexity values of each area within the pair ofphotos, thus producing a difference complexity metric for the pair ofphotos. The said complexity metric of each photo along with the photo isstored within the external database 80 for further evaluation.Additionally, according to the present embodiment, the sorting device 50sorts the areas within the photos according to their complexity valueand sends to the user interface 30 the relevant information including,the relevant fragment and the recognition and analysis of the fragmentreceived from the ORAS. Thus, the user interface 30 displays therelevant areas extracted from both photos and the difference recognizedand analyzed by the ORAS.

The person skilled in the art will appreciate that what has been shownis not limited to the description above. Those skilled in the art towhich this invention pertains will appreciate many modifications andother embodiments of the invention. It will be apparent that the presentinvention is not limited to the specific embodiments disclosed and thosemodifications and other embodiments are intended to be included withinthe scope of the invention. Although specific terms are employed herein,they are used in a generic and descriptive sense only and not forpurposes of limitation. The invention, therefore, should not berestricted, except to the following claims and their equivalents.

1. A method for analysis of aerial photos, the method comprising:receiving an aerial photo; dividing the aerial photo to equal sizedareas of two dimensional arrays of pixels; calculating complexity valuesfor the equal sized areas within the aerial photo received; sorting theareas within the aerial photo in accordance with the complexity values;displaying the aerial photo and analysis results of the complexityvalues; and wherein said complexity values give indication regarding thenumber of combinations of bit patterns appearing in the equal sized arearelative to the number of possible combinations that could appear in theequal sized area.
 2. The method of claim 1 further comprising comparingcomplexity values of at least two aerial photos of the same locationtaken at different times.
 3. A system for analysis of aerial photos, thesystem comprises: an input device for receiving aerial photos; acomputing device for dividing the aerial photo to equal sized areas oftwo dimensional arrays of pixels and calculating complexity values forthe equal sized areas in the aerial photos; a computing device forsorting complexity values of aerial photos; and a storage device forstoring an internal database for storing the aerial photos; and whereinsaid complexity values give indication regarding the number ofcombinations of bit patterns appearing in the equal sized area relativeto the number of possible combinations that could appear in the equalsized area.
 4. The system of claim 3 further comprising a comparatordevice for comparing complexity values of at least two photos taken ofthe same location at different times.